Mining activities in the Kenyan Marble Quarries (KMQ) are a potential source of atmospheric pollution, raising health concerns for the local population. This study aims to examine the extent to which marble mining contributes to atmospheric trace gas concentrations, using remote sensing and GIS-based machine learning techniques to map and analyse gaseous compositions. The investigation covers KMQ and Kajiado town, spanning 342 km2, and examines changes in patterns of land use and land cover (LULC), climate variables, and gaseous pollutants over five years (2019–2024). Sentinel-5P data for SO2, NO2, CO, O3, and CH4 were processed using Google Earth Engine, and LULC changes were detected through Supervised Vector Machine classification. Climate data were obtained from NASA Power. The results indicate that mining and agriculture are the dominant land uses, and that atmospheric gases are relatively uniformly distributed across the area. Strong climatic influences were observed: humidity, wind, precipitation, and solar radiation show varying correlations with trace gas concentrations, which are consistently higher during the dry season. Overall, the findings suggest that marble mining contributes minimally to the levels of the analysed gases, with vegetation clearing and agricultural activities also serving as significant drivers of gaseous variation across the region.
Ancho et al. (Thu,) studied this question.